Home-based self-employment: combining personal, household and employment influences

Despite the significant economic, innovative and social contributions of home-based self-employment, it is an under-researched and under-theorised area. We address this gap by drawing from established entrepreneurial theory to propose and validate a more complete theoretical model that combines personal, household and employment influences. We validate our proposed model by drawing on quantitative data from a large-scale, longitudinal, UK-based, social studies dataset. Our validated model demonstrates how and why antecedent and current household and employment factors, but not personal factors, associated with being home-based interact and provide constitutive affordances that result in a setting for self-employment that is unique in more fundamental ways than simply the home location of the business. Despite being responsible for some of the world’s most innovative and successful businesses, home-based businesses are often denigrated as lacking ambition or growth potential. The results of our analysis vindicate the choices of the home-based self-employed, by demonstrating that basing a business in the home is a rational choice based on an intersection of household and employment characteristics. The data used in this study predates the COVID-19 pandemic. However, it is expected that home-based self-employment will grow significantly following the pandemic in response to increasing acceptance of home-working. It therefore behoves entrepreneurship scholars to have a robust understanding of this previously overlooked type of self-employment if we are to be able to provide guidance to policymakers and self-employment support services

Shrinkage Priors for Isotonic Probability Vectors and Binary Data Modeling

This paper outlines a new class of shrinkage priors for Bayesian isotonic regression modeling a binary outcome against a predictor, where the probability of the outcome is assumed to be monotonically non-decreasing with the predictor. The predictor is categorized into a large number of groups, and the set of differences between outcome probabilities in consecutive categories is equipped with a multivariate prior having support over the set of simplexes. The Dirichlet distribution, which can be derived from a normalized cumulative sum of gamma-distributed random variables, is a natural choice of prior, but using mathematical and simulation-based arguments, we show that the resulting posterior can be numerically unstable, even under simple data configurations. We propose an alternative prior motivated by horseshoe-type shrinkage that is numerically more stable. We show that this horseshoe-based prior is not subject to the numerical instability seen in the Dirichlet/gamma-based prior and that the posterior can estimate the underlying true curve more efficiently than the Dirichlet distribution. We demonstrate the use of this prior in a model predicting the occurrence of radiation-induced lung toxicity in lung cancer patients as a function of dose delivered to normal lung tissue

Using GIS to Prioritize Green Infrastructure Installation Strategies in an Urbanized Watershed

2014 S.C. Water Resources Conference - Informing Strategic Water Planning to Address Natural Resource, Community and Economic Challenge

Hierarchical Bin Buffering: Online Local Moments for Dynamic External Memory Arrays

Local moments are used for local regression, to compute statistical measures such as sums, averages, and standard deviations, and to approximate probability distributions. We consider the case where the data source is a very large I/O array of size n and we want to compute the first N local moments, for some constant N. Without precomputation, this requires O(n) time. We develop a sequence of algorithms of increasing sophistication that use precomputation and additional buffer space to speed up queries. The simpler algorithms partition the I/O array into consecutive ranges called bins, and they are applicable not only to local-moment queries, but also to algebraic queries (MAX, AVERAGE, SUM, etc.). With N buffers of size sqrt{n}, time complexity drops to O(sqrt n). A more sophisticated approach uses hierarchical buffering and has a logarithmic time complexity (O(b log_b n)), when using N hierarchical buffers of size n/b. Using Overlapped Bin Buffering, we show that only a single buffer is needed, as with wavelet-based algorithms, but using much less storage. Applications exist in multidimensional and statistical databases over massive data sets, interactive image processing, and visualization

Investigation of the TOCA1-Cdc42 interaction

Transducer of Cdc42-dependent actin assembly protein 1 (TOCA1) is an effector of the Rho family small G protein Cdc42. It contains a membrane-deforming F-BAR domain as well as a Src homology 3 (SH3) domain and a G protein-binding homology region 1 (HR1) domain. TOCA1 binding to Cdc42 leads to actin rearrangements, which are thought to be involved in processes such as endocytosis, filopodia formation, and cell migration. We have solved the structure of the HR1 domain of TOCA1, providing the first structural data for this protein. We have found that the TOCA1 HR1, like the closely related CIP4 HR1, has interesting structural features that are not observed in other HR1 domains. We have also investigated the binding of the TOCA HR1 domain to Cdc42 and the potential ternary complex between Cdc42 and the G protein-binding regions of TOCA1 and a member of the Wiskott-Aldrich syndrome protein family, N-WASP. TOCA1 binds Cdc42 with micromolar affinity, in contrast to the nanomolar affinity of the N-WASP G protein-binding region for Cdc42. NMR experiments show that the Cdc42-binding domain from N-WASP is able to displace TOCA1 HR1 from Cdc42, whereas the N-WASP domain but not the TOCA1 HR1 domain inhibits actin polymerization. This suggests that TOCA1 binding to Cdc42 is an early step in the Cdc42-dependent pathways that govern actin dynamics, and the differential binding affinities of the effectors facilitate a handover from TOCA1 to N-WASP, which can then drive recruitment of the actin-modifying machinery.JRW is supported by a Herchel Smith studentship. JLG is supported by a Wellcome Trust Research Career Development Fellowship (WT095829AIA), European Research Council Starting Grant (281971) and Gurdon Institute funding provided by the Wellcome Trust (092096) and CRUK (C6946/A14492). HMF is supported by a Wellcome Trust PhD Studentship (WT099740Z12Z). We would like to thank Dr A Walrant for help with the pyrene actin assays and liposome preparation. We are also grateful to Dr J.R. Peterson (Fox Chase Cancer Center) for human TOCA1 clones.This is the final version of the article. It first appeared from the American Society for Biochemistry and Molecular Biology via http://dx.doi.org/10.1074/jbc.M116.72429

Using RNA-seq to characterize responses to 4 hydroxyphenylpyruvate dioxygenase (HPPD) inhibitor herbicide resistance in waterhemp (Amaranthus tuberculatus)

Background: Waterhemp (Amaranthus tuberculatus (Moq.) J.D. Sauer) is a problem weed commonly found in the Midwestern United States that can cause crippling yield losses for both maize (Zea mays L.) and soybean (Glycine max L. Merr). In 2011, 4-hydroxyphenylpyruvate-dioxygenase (HPPD, EC 1.13.11.27) inhibitor herbicide resistance was first reported in two waterhemp populations. Since the discovery of HPPD-herbicide resistance, studies have identified the mechanism of resistance and described the inheritance of the herbicide resistance. However, no studies have examined genome-wide gene expression changes in response to herbicide treatment in herbicide resistant and susceptible waterhemp. Results: We conducted RNA-sequencing (RNA-seq) analyses of two waterhemp populations (HPPD-herbicide resistant and susceptible), from herbicide-treated and mock-treated leaf samples at three, six, twelve, and twenty-four hours after treatment (HAT). We performed a de novo transcriptome assembly using all sample sequences. Following assessments of our assembly, individual samples were mapped to the de novo transcriptome allowing us to identify transcripts specific to a genotype, herbicide treatment, or time point. Our results indicate that the response of HPPDherbicide resistant and susceptible waterhemp genotypes to HPPD-inhibiting herbicide is rapid, established as soon as 3 hours after herbicide treatment. Further, there was little overlap in gene expression between resistant and susceptible genotypes, highlighting dynamic differences in response to herbicide treatment. In addition, we used stringent analytical methods to identify candidate single nucleotide polymorphisms (SNPs) that distinguish the resistant and susceptible genotypes. Conclusions: The waterhemp transcriptome, herbicide-responsive genes, and SNPs generated in this study provide valuable tools for future studies by numerous plant science communities. This collection of resources is essential to study and understand herbicide effects on gene expression in resistant and susceptible weeds. Understanding how herbicides impact gene expression could allow us to develop novel approaches for future herbicide development. Additionally, an increased understanding of the prolific traits intrinsic in weed success could lead to crop improvement

How do lizard niches conserve, diverge or converge? Further exploration of saurian evolutionary ecology

Background: Environmental conditions on Earth are repeated in non-random patterns that often coincide with species from different regions and time periods having consistent combinations of morphological, physiological and behavioral traits. Observation of repeated trait combinations among species confronting similar environmental conditions suggest that adaptive trait combinations are constrained by functional tradeoffs within or across niche dimensions. In an earlier study, we assembled a high-resolution database of functional traits for 134 lizard species to explore ecological diversification in relation to five fundamental niche dimensions. Here we expand and further examine multivariate relationships in that dataset to assess the relative influence of niche dimensions on the distribution of species in 6-dimensional niche space and how these may deviate from distributions generated from null models. We then analyzed a dataset with lower functional-trait resolution for 1023 lizard species that was compiled from our dataset and a published database, representing most of the extant families and environmental conditions occupied by lizards globally. Ordinations from multivariate analysis were compared with null models to assess how ecological and historical factors have resulted in the conservation, divergence or convergence of lizard niches. Results: Lizard species clustered within a functional niche volume influenced mostly by functional traits associated with diet, activity, and habitat/substrate. Consistent patterns of trait combinations within and among niche dimensions yielded 24 functional groups that occupied a total niche space significantly smaller than plausible spaces projected by null models. Null model tests indicated that several functional groups are strongly constrained by phylogeny, such as nocturnality in the Gekkota and the secondarily acquired sit-and-wait foraging strategy in Iguania. Most of the widely distributed and species-rich families contained multiple functional groups thereby contributing to high incidence of niche convergence. Conclusions: Comparison of empirical patterns with those generated by null models suggests that ecological filters promote limited sets of trait combinations, especially where similar conditions occur, reflecting both niche convergence and conservatism. Widespread patterns of niche convergence following ancestral niche diversification support the idea that lizard niches are defined by trait-function relationships and interactions with environment that are, to some degree, predictable and independent of phylogeny.Fil: Pelegrin, Nicolas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Winemiller, Kirk Owen. Texas A&M University; Estados UnidosFil: Vitt, Laurie J.. University Of Oklahoma; Estados UnidosFil: Fitzgerald, Daniel B.. United States Geological Survey; Estados UnidosFil: Pianka, Eric R. University of Texas at Austin; Estados Unido

Gravitational waves from inspiraling compact binaries: Validity of the stationary-phase approximation to the Fourier transform

We prove that the oft-used stationary-phase method gives a very accurate expression for the Fourier transform of the gravitational-wave signal produced by an inspiraling compact binary. We give three arguments. First, we analytically calculate the next-order correction to the stationary-phase approximation, and show that it is small. This calculation is essentially an application of the steepest-descent method to evaluate integrals. Second, we numerically compare the stationary-phase expression to the results obtained by Fast Fourier Transform. We show that the differences can be fully attributed to the windowing of the time series, and that they have nothing to do with an intrinsic failure of the stationary-phase method. And third, we show that these differences are negligible for the practical application of matched filtering.Comment: 8 pages, ReVTeX, 4 figure

Helical ensembles outperform ideal helices in molecular replacement

The conventional approach in molecular replacement (MR) is the use of a related structure as a search model. However, this is not always possible as the availability of such structures can be scarce for poorly characterised families of proteins. In these cases, alternative approaches can be explored, such as the use of small ideal fragments that share high albeit local structural similarity with the unknown protein. Earlier versions of AMPLE enabled the trialling of a library of ideal helices, which worked well for largely helical proteins at suitable resolution. Here we explore the performance of libraries of helical ensembles created by clustering helical segments. The impacts of different B-factor treatments and different degrees of structural heterogeneity are explored. We observed a 30% increase in the number of solutions obtained by AMPLE when using this new set of ensembles compared to performance with ideal helices. The boost of performance was notable across three different folds: transmembrane, globular and coiled-coil structures. Furthermore, the increased effectiveness of these ensembles was coupled to a reduction of the time required by AMPLE to reach a solution. AMPLE users can now take full advantage of this new library of search models by activating the “helical ensembles” mode

Whole-Genome Sequencing and Concordance Between Antimicrobial Susceptibility Genotypes and Phenotypes of Bacterial Isolates Associated with Bovine Respiratory Disease.

Extended laboratory culture and antimicrobial susceptibility testing timelines hinder rapid species identification and susceptibility profiling of bacterial pathogens associated with bovine respiratory disease, the most prevalent cause of cattle mortality in the United States. Whole-genome sequencing offers a culture-independent alternative to current bacterial identification methods, but requires a library of bacterial reference genomes for comparison. To contribute new bacterial genome assemblies and evaluate genetic diversity and variation in antimicrobial resistance genotypes, whole-genome sequencing was performed on bovine respiratory disease-associated bacterial isolates (Histophilus somni, Mycoplasma bovis, Mannheimia haemolytica, and Pasteurella multocida) from dairy and beef cattle. One hundred genomically distinct assemblies were added to the NCBI database, doubling the available genomic sequences for these four species. Computer-based methods identified 11 predicted antimicrobial resistance genes in three species, with none being detected in M. bovis While computer-based analysis can identify antibiotic resistance genes within whole-genome sequences (genotype), it may not predict the actual antimicrobial resistance observed in a living organism (phenotype). Antimicrobial susceptibility testing on 64 H. somni, M. haemolytica, and P. multocida isolates had an overall concordance rate between genotype and phenotypic resistance to the associated class of antimicrobials of 72.7% (P < 0.001), showing substantial discordance. Concordance rates varied greatly among different antimicrobial, antibiotic resistance gene, and bacterial species combinations. This suggests that antimicrobial susceptibility phenotypes are needed to complement genomically predicted antibiotic resistance gene genotypes to better understand how the presence of antibiotic resistance genes within a given bacterial species could potentially impact optimal bovine respiratory disease treatment and morbidity/mortality outcomes